Evolution by Wireless Network Operators (WNOs) from Second Generation (2G) to Third Generation (3G) wireless networks has produced an explosion in demand for services enabled by 3G wireless networks, while at the same time increasing network complexity. In order to prevent network under-provisioning resulting in quality-of-service (QoS) degradation, and network over-provisioning resulting in wasted capital, WNOs need to be able to accurately forecast network growth to ensure just-in-time capacity provisioning, as well as to ensure that the network remains optimized with respect to QoS. Unfortunately, existing methodologies for performing wireless network growth planning are inefficient and inaccurate, and, therefore, costly.
Existing wireless network growth planning methodologies tend to be manual and, thus, time consuming and error prone. Existing methodologies spread network growth analysis across engineering groups, thereby increasing risks of inconsistency due to different sets of localized rules used by different engineering groups, e.g., wireless engineers perform network capacity analysis for the radio access network while switch engineers perform network capacity analysis for the core switching network. Furthermore, existing methodologies are merely simplistic trending functions that use average values for similar network elements, failing to include network configuration information and cross-component utilization effects that account for network component interdependencies.